مقاله انگلیسی رایگان در مورد پیشرفته-Ant-AODV برای انتخاب مسیر بهینه – الزویر 2018

Selection of an optimal path is a challenging issue in Mobile Ad-hoc network (MANET). This paper proposes a new mechanism for route selection combining Ad-hoc On-Demand Distance Vector (AODV) protocol with Ant Colony Optimization (ACO) to improve Quality of Service (QoS) in MANET. Based on the mechanism of ant colony with AODV, the finest route for data delivery is selected using pheromone value of the path. In the proposed work, pheromone value of a route is calculated based on end to end reliability of the path, congestion, number of hops and residual energy of the nodes along the path. The path which has highest pheromone value will be selected for transmission of the data packet. The simulation result shows that the proposed scheme outperforms AODV, Dynamic Source Routing (DSR) and Enhanced-Ant-DSR routing algorithms.

INTRODUCTION

Ad-hoc networks are collection of mobile nodes communicating with each other using wireless media without any fixed infrastructure. Mobile ad-hoc network (MANET) (Pahlavan and Krishnamurthy, 2011; Giordano, 2002; Yadav and Rishiwal, 2011) dynamically forms a network without any support of central management. Because of this dynamic nature, routing in MANET is difficult when some QoS requirements need to be satisfied. There are many routing protocols that can fulfill various QoS requirements but none of those protocols supports those requirements altogether. In this paper, an enhanced technique combining Ad-hoc On Demand Distance Vector (AODV) with Ant Colony Optimization (ACO) (Dorigo and Stu1etzle, 2004) mechanism is developed. In proposed technique, before a node sends a data packet to another node, like AODV, it finds out the route to the destination. For finding the route, the sender node broadcasts Route Request packets (named as ReqAnt packets) in the network. This is same as biological ants which first spread out in many directions for searching food. After finding the food source, they deposit pheromone on their way back to the home, so that other ants can get knowledge about the path. Similarly, in the proposed technique the ReqAnt packets are broadcasted in the network. They collect information about the path namely: end to end reliability of the route, congestion along the route, residual energy of the node along the route and length of the route. After receiving the ReqAnt packet, the destination calculates pheromone count of a route considering the path information stored in ReqAnt and sends back the RepAnt (Route Reply packet). The route of highest pheromone count is considered for routing data packets. The ACO based Enhanced AODV outperforms AODV and other ACO routing schemes in various scenarios. Organization of the paper is as follows. Section 2 presents the problem statement of the research work. Section 3 discusses some of the existing schemes. The proposed enhanced ANT AODV scheme is presented in section 4. In section 5 the simulation results of the proposed scheme is compared with AODV, DSR and enhanced ANT DSR. Finally, in section 6 conclusion and future work has been presented.